Object Detection
Showing 36 of 80 projects
TensorFlow implementation of YOLO for real-time object detection using pretrained YOLO_small, YOLO_tiny, and YOLO_face models.
A deep learning pipeline for 3D object detection from RGB-D data by combining 2D detectors with PointNet-based 3D processing.
An all-in-one framework for training state-of-the-art computer vision models, covering pretraining, fine-tuning, and distillation.
A general-purpose PyTorch codebase for 3D object detection with state-of-the-art model implementations and multi-dataset support.
An example Android project demonstrating how to build and integrate TensorFlow for object detection using the camera.
A curated collection of open-source computer vision pre-trained models across TensorFlow, Keras, PyTorch, Caffe, and MXNet frameworks.
A Python library for 2D/3D object detection and instance segmentation in microscopy images using star-convex shapes.
A deep learning system for detecting known objects and estimating their 6-DoF pose from RGB images.
A library of modular computer vision components built on Keras 3, supporting TensorFlow, JAX, and PyTorch backends.
High-level TensorFlow network definitions with pre-trained weights for easy integration into existing ML workflows.
Deep learning inference nodes for ROS/ROS2 with support for NVIDIA Jetson devices and TensorRT.
A visible-infrared paired dataset for low-light vision tasks like pedestrian detection, image fusion, and image-to-image translation.
Real-time object detection on Android using YOLO with TensorFlow, detecting 20 object classes from the Pascal VOC dataset.
Build fully-functioning computer vision and object detection models with PyTorch in just 5 lines of code.
An advanced iOS camera engine library built in Swift on top of AVFoundation for easy camera customization and special capture features.
A curated list of popular deep learning models for image classification, segmentation, and detection with key performance metrics.
A curated collection of robotics and computer vision datasets for research and development.
A deep learning framework for detecting and localizing upper-body, lower-body, and full-body clothes in fashion images.
A PyTorch implementation of TResNet, a high-performance convolutional neural network architecture optimized for GPU training and inference.
A ROS-based object detection and pose estimation library for 2D and 3D applications using OpenCV.
A neural network for object detection using multi-level fusion of camera and radar data, built on Keras RetinaNet.
A ROS library for LiDAR point cloud segmentation, enabling ground removal and object clustering for autonomous vehicle perception.
A Python toolbox for image segmentation featuring superpixel segmentation, object center detection, and region growing with shape priors.
An easy-to-use C# deep learning library with support for multiple backends including TensorFlow, PyTorch, and CUDA/OpenCL.
A re-implementation of the SPP-net object detection algorithm using spatial pyramid pooling in deep convolutional networks for visual recognition.
A real-time RGB-based pipeline for object detection and 6D pose estimation using a denoising autoencoder trained on simulated 3D views.
A Docker-based image annotation tool for bounding box labeling with auto-labeling support, designed for deep learning training.
ROS 2 wrapper for Stereolabs ZED cameras, providing access to depth, point clouds, object detection, and spatial mapping.
A TensorFlow-based object detection model that localizes and identifies multiple objects in images using SSD MobileNet V1 or Faster R-CNN ResNet101.
An open-source full-stack ROS-based software for self-driving applications in low-speed urban environments.
A centralized Python framework for agricultural machine learning, providing access to public datasets, benchmarks, pretrained models, and synthetic data generation.
An open-source tool to detect and blur faces and license plates in images for privacy compliance, using TensorFlow object detection.
A PyTorch framework for deep learning on point clouds, providing a modular and reproducible foundation for 3D vision tasks.
ROS package for sensor processing, object detection, tracking, and evaluation using the KITTI Vision Benchmark dataset.
A Docker container for face detection using Faster R-CNN deep learning, processing videos and images with bounding box outputs.
A YOLO-based object detection system specifically trained to identify DJI drones in images and video.
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